Independent intelligence. Connected business.
More context.
Less friction.
Your business has the knowledge. Give AI the context to use it — through one vendor-neutral layer for shared intelligence, trusted connections and cost-aware decisions.
INTELLIGENCE, IN FLOW
One connected layer. Not another silo.
The missing connection
A better model is only part of the answer.
AI cannot understand a business it only sees in fragments. Trust and cost are systems challenges — across your data, tools, models and decisions.
A shared understanding. A considered response.
Connect the context
Make relevant business knowledge reusable across applications and agents.
Keep evidence in view
Bring sources and uncertainty into the decision, rather than hiding them.
Make every request count
Coordinate context handling, model choice and governed tool access.
Connect what your business knows to what your AI does.
One gateway. Four complementary services.
Intelligence works better together.
A connected system with clear responsibilities. Explore each service to see its role — and the value of bringing them together.
Shared business memory
Your business, in context.
Turn scattered business information into reusable knowledge, with sources, confidence and time-aware context. Give applications and agents a shared foundation to work from.
Less repeated discovery. A richer understanding of the business behind each request.
Conceptual responsibilities, not a fixed execution order. MCP connects tools; Knowledge supplies context; Optimizer makes request decisions; Model Gateway handles model execution.
Trust, made inspectable
Confidence should come with evidence.
Revimize is designed to make the whole path inspectable: what the system knew, how confident it was, what it checked, and who approved the next action. A result can expose its disposition, confidence band, evidence quality, freshness, grounding coverage, validation status, limitations and citations.
01
Calibrated confidence
Confidence is measured against held-out outcomes for the tenant and use case. Calibrated, fallback and uncalibrated states stay distinguishable; a result is never labelled calibrated without an approved artifact.
02
Pre-inference grounding
Before generation or action, a sufficiency gate checks authority, freshness, consistency and permission. Missing or conflicting evidence routes to clarify, retrieve more, review or block. If the gate cannot run, the system fails closed to a qualified response or a request for context.
03
Risk-tier gating
The consequence of a decision sets the operating point. Informational answers, recommendations, reversible actions and irreversible actions need different evidence, latency and approval budgets.
04
Post-inference verification
Material claims are checked against cited source spans. Supported, partial, unsupported and contradicted claims remain separate, and citation validity is checked before a result proceeds.
05
Human oversight
Review, dispute and approval paths keep a human in the loop. Higher-risk actions require the right approver and separation of duties; self-approval is blocked.
06
Audit and source lifecycle
Expiry, revocation, permission loss and contradictions re-gate dependent results. A trust trace records the disposition, evidence, versions and review history for inspection.
07
Tenant scope and boundaries
Permission-aware retrieval and tenant boundaries apply before evidence is scored. Raw tenant content is not used for shared or cross-tenant learning; retention and deletion rules are explicit.
08
Continuous evaluation
Golden datasets, retrieval-quality monitoring, adversarial tests and outcome feedback support calibration, promotion and rollback. A control is proven by evidence, not by code alone.
One inspectable path
- Ground
- Gate
- Infer
- Verify
- Review
- Audit
Trust controls depend on configuration and deployment. This page describes product design intent, not a certification, a guarantee of accuracy or a claim that every control is live today. Current implementation status is tracked separately.
Built for the business around AI.
What better context makes possible.
Make your existing AI more useful.
Bring broader business context to your applications without building every part of the intelligence infrastructure yourself.
- Reuse business knowledge across teams and applications.
- Keep sources and uncertainty visible when decisions matter.
- Make model and tool connections easier to govern.
The longer-term vision
An independent context, intelligence and verification layer that agents can consult before they reason or act.
Strategic direction, not a promise that every future capability is available today.
Follow one decision
An unhappy customer. A bigger picture.
A support issue is not the whole customer story. Trace how the four services can contribute to a more informed response.
Illustrative walkthrough — fictional evidence, no live data, model calls or tool execution. This is not a product benchmark.
MCP Gateway
Access the approved tools.
A configured connector provides permitted access to customer-system tools. Access is deliberate, not assumed.
Approved customer-system connection
Try a different condition
ILLUSTRATIVE DECISION
Prioritise a coordinated review.
Consider the support issue together with renewal context and changing engagement. Ask the account team to review the evidence before choosing an action.
Human review remains part of the decision.
Talk to us
See what connected context can do for your business.
Book a short conversation with the Revimize team. We will discuss your systems, your AI priorities and where shared context can help.
Book a demo